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Check On-Time Performance of Domestic Airlines Using Random Forest Machine Learning Analysis

Author

Listed:
  • Ariyono Setiawan

    (Akademi Penerbang Indonesia Banyuwangi.)

  • Efendi Efendi

    (Akademi Penerbang Indonesia Banyuwangi.)

  • Ahmad Mubarok

    (Akademi Penerbang Indonesia Banyuwangi.)

  • Kukuh Tri Prasetyo

    (Akademi Penerbang Indonesia Banyuwangi.)

  • Untung Lestari Nur Wibowo

    (Akademi Penerbang Indonesia Banyuwangi.)

Abstract

This study aims to analyze the On-Time Performance on domestic flights in Indonesia using the Random Forest machine learning analysis method. The purpose of this study is to predict On-Time Performance on domestic flights with high accuracy. The data used in this study are questionnaire data and factors that affect On-Time Performance on domestic flights in Indonesia. The results showed that the Random Forest model can produce On-Time Performance predictions on domestic flights with a high level of accuracy. Factors such as ground handling services, weather, and technical operations have a significant influence on On-Time Performance on domestic flights. The implication of this research is that it can help airlines optimize flight schedules and minimize flight delays, thus providing satisfaction to passengers

Suggested Citation

  • Ariyono Setiawan & Efendi Efendi & Ahmad Mubarok & Kukuh Tri Prasetyo & Untung Lestari Nur Wibowo, 2023. "Check On-Time Performance of Domestic Airlines Using Random Forest Machine Learning Analysis," Technium Social Sciences Journal, Technium Science, vol. 43(1), pages 570-583, May.
    • Handle: RePEc:tec:journl:v:43:y:2023:i:1:p:570-583
    DOI: 10.47577/tssj.v43i1.8792
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    More about this item

    Keywords

    On Time Performance; Machine Learning; Random Forest;
    All these keywords.

    JEL classification:

    • R00 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General - - - General
    • Z0 - Other Special Topics - - General

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